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Purpose The use of Lipiodol and cone beam computed tomography (CT) has facilitated the generation of patient-specific planning target volumes (PTV) to reduce irradiation of normal tissue. However, injecting Lipiodol to demarcate the target volume is an invasive procedure. Center of bladder (COB) and bladder wall surface (BWS) encompassed by the clinical target volume (CTV) are proposed to be the alternative noninvasive surrogates. This study examines the impact of using these 3 surrogates for image registration on the resultant geometry of patient-specific PTVs. Methods and materials Twenty bladder cancer patients who had Lipiodol injection before planning CT were included. Lipiodol, CTV, and bladder were delineated on the planning CT. In addition, CTVs were delineated on 5 cone beam CT scans from each patient. Cone beam CT scans were registered to planning CT using Lipiodol, COB, and BWS to generate Lipiodol-PTV, COB-PTV, and BWS-PTV. Using Lipiodol as the reference, the difference in the 2-dimensional/3-dimensional displacement values and the geometry of the resultant PTVs were quantified. Results A total of 1200 displacement values and 60 volumes were included for analysis. The overall median and standard deviation (SD) of the 3-dimensional displacement (mm) measured by Lipiodol, BWS, and COB are 25 (SD, 15), 24 (SD, 14), and 21 (SD, 15), respectively. Lipiodol-PTV has the smallest mean volume, followed by BWS-PTV and COB-PTV. BWS-PTV was more geometrically similar to Lipiodol-PTV when compared with COB-PTV. Six of 20 COB-PTVs who had CTV located at either the dome or the base of the bladder were larger than the corresponding Lipiodol-PTV by more than 20%. Conclusion Lipiodol is the optimal image registration surrogate for partial bladder radiation therapy. However, for patients who are contraindicated for Lipiodol injection, BWS is the preferred noninvasive surrogate because the derived PTV has a smaller geometric variation from the Lipiodol-PTV when compared with COB, especially when the CTV was located at the dome or the base of the bladder.

All studies to date have evaluated the dosimetric effect of bladder deformation using an organ model that includes the dose to the urine. This research reconstructed bladder dose using both hollow and solid organ models, to determine if dose/volume differences exist.35 prostate IMRT patients were selected, who had received 78Gy in 39 fractions and full bladder instructions. Biomechanical modelling and finite element analysis were used to reconstruct bladder dose (solid and hollow organ model) using every third CBCT throughout the treatment course.Reconstructed dose (ReconDose) was 11.3Gy greater than planned dose (planDose) with a hollow bladder model (p0.001) and 12.3Gy greater with a solid bladder model (p0.0001). Median reconstructed volumes within the 30Gy, 65Gy and 78Gy isodoses were 3-4 times larger with the solid organ model (p0.0001). The difference between planning bladder volume and median treatment volume was associated with the difference between the planDose and reconDose below 78Gy (R(2)0.61).Substantial differences exist between planned and reconstructed bladder dose, associated with the differences in bladder filling between planning and treatment. Dose reconstructed using a solid bladder model over-reports the volume of bladder within key isodose levels and overestimates the differences between planned and reconstructed dose. Dose reconstruction with a hollow organ model is recommended if the goal is to associate that dose with toxicity.

Biomechanical-based deformable image registration is conducted on the head and neck region. Patient specific 3D finite element models consisting of parotid glands (PG), submandibular glands (SG), tumor, vertebrae (VB), mandible, and external body are used to register pre-treatment MRI to post-treatment MR images to model the dose response using image data of five patients. The images are registered using combinations of vertebrae and mandible alignments, and surface projection of the external body as boundary conditions. In addition, the dose response is simulated by applying a new loading technique in the form of a dose-induced shrinkage using the dose-volume relationship. The dose-induced load is applied as dose-induced shrinkage of the tumor and four salivary glands. The Dice Similarity Coefficient (DSC) is calculated for the four salivary glands, and tumor to calculate the volume overlap of the structures after deformable registration. A substantial improvement in the registration is found by including the dose-induced shrinkage. The greatest registration improvement is found in the four glands where the average DSC increases from 0.53, 0.55, 0.32, and 0.37 to 0.68, 0.68, 0.51, and 0.49 in the left PG, right PG, left SG, and right SG, respectively by using bony alignment of vertebrae and mandible (M), body (B) surface projection and dose (D) (VB+M+B+D).

Chronic lung allograft dysfunction (CLAD) reduces long-term graft survival. It is important to distinguish CLAD subtypes: bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS) as RAS has a worse prognosis and accurate subtyping could facilitate targeted treatments. However, the current diagnosis of CLAD subtypes is based on pulmonary function test (PFT) results that reflect global estimates of lung function; anatomical modeling based on computed tomography (CT) has the potential to provide detailed analysis of global and regional lung function. The purpose of this study is to evaluate the utility of CT-based anatomical modeling for the identification of RAS. This retrospective study included 51 patients (CLAD: 17 BOS and 17 RAS, control: 17 No-CLAD). CT data were assessed using a biomechanical model-based platform (MORFEUS) to characterize changes in lung deformation between baseline and disease onset. Lung deformation demonstrated high sensitivity and specificity (>80%) in differentiating RAS from BOS (P

Purpose: Deformable image registration (DIR) allows modeling of livertumors on respiratory correlated (4D) imaging. The mid‐position CT was reconstructed for liverSBRT plans using DIR, and the potential for dose‐escalation was investigated. Methods: Thirty patients were planned clinically with IMRT for 27–48 Gy in 6 fractions on static exhale 4DCT with PTVs encompassing the breathing amplitude. For research, exhale 4DCT was deformed to the inhale 4DCT using biomechanical DIR. The mid‐position CT was created by applying a percentage (the time‐averaged normalized position between exhale and inhale calculated from daily 4D cone‐beam CT) to this deformation map, assuming a linear trajectory. A probability‐based PTV margin, using patient‐specific breathing amplitude from DIR of 4DCT, was created around the GTV on the mid‐position CT where IMRT was re‐optimized. Dose was maximally escalated according to clinical protocol (e.g. liver NTCP

Purpose The widespread use of intensity modulated radiation therapy (IMRT) for cervical cancer has been limited by internal target and normal tissue motion. Such motion increases the risk of underdosing the target, especially as planning margins are reduced in an effort to reduce toxicity. This study explored 2 adaptive strategies to mitigate this risk and proposes a new, automated method that minimizes replanning workload. Methods and Materials Thirty patients with cervical cancer participated in a prospective clinical study and underwent pretreatment and weekly magnetic resonance (MR) scans over a 5-week course of daily external beam radiation therapy. Target volumes and organs at risk (OARs) were contoured on each of the scans. Deformable image registration was used to model the accumulated dose (the real dose delivered to the target and OARs) for 2 adaptive replanning scenarios that assumed a very small PTV margin of only 3 mm to account for setup and internal interfractional motion: ( 1 ) a preprogrammed, anatomy-driven midtreatment replan (A-IMRT); and ( 2 ) a dosimetry-triggered replan driven by target dose accumulation over time (D-IMRT). Results Across all 30 patients, clinically relevant target dose thresholds failed for 8 patients (27%) if 3-mm margins were used without replanning. A-IMRT failed in only 3 patients and also yielded an additional small reduction in OAR doses at the cost of 30 replans. D-IMRT assured adequate target coverage in all patients, with only 23 replans in 16 patients. Conclusions A novel, dosimetry-triggered adaptive IMRT strategy for patients with cervical cancer can minimize the risk of target underdosing in the setting of very small margins and substantial interfractional motion while minimizing programmatic workload and cost.

Purpose To characterize nonrespiratory stomach motion in the fasting state and postprandial. Methods and materials Ten healthy volunteers underwent 2-dimensional Fiesta cine magnetic resonance imaging studies in 30-second voluntary breath hold, in axial, coronal, and 2 oblique planes while fasting, and 5, 15, 30, 45, and 60 minutes postmeal. Each stomach contour was delineated and sampled with 200 points. Matching points were found for all contours in the same 30-second acquisition. Using deformable parametric analysis (Matlab, version 7.1), mean magnitude, and standard deviation of displacement of each point were determined for each patient. Maximal, minimal, and median population values in 6 cardinal, and in any direction, were calculated. Results The median of mean displacements for the baseline position of each point was small and rarely exceeded 1.1 mm; greatest value was 1.6 mm superior–inferior. Median displacement (pooled across time) in the right–left, superior–inferior, and anterior–posterior directions was 0.3 (range, −0.7 to 1.3), 0.8 (−0.4 to 2.4), and 0.3 (−1.1 to 1.6) mm, respectively. Fasting and postprandial standard deviation did not differ. Conclusions Nonrespiratory stomach displacement is small and stomach position is stable after a small, standard meal. Radiation therapy may be delivered at any time within the first hour after eating without significant compromise of planned planning target volumes.

The dosimetric impact of dose probability based planning target volume (PTV) margins for liver cancer patients receiving stereotactic body radiation therapy (SBRT) was compared with standard PTV based on the internal target volume (ITV). Plan robustness was evaluated by accumulating the treatment dose to ensure delivery of the intended plan.Twenty patients planned on exhale CT for 27 to 50 Gy in 6 fractions using an ITV-based PTV and treated free-breathing were retrospectively evaluated. Isotoxic, dose escalated plans were created on midposition computed tomography (CT), representing the mean breathing position, using a dose probability PTV. The delivered doses were accumulated using biomechanical deformable registration of the daily cone beam CT based on liver targeting at the exhale or mean breathing position, for the exhale and midposition CT plans, respectively.The dose probability PTVs were on average 38% smaller than the ITV-based PTV, enabling an average ± standard deviation increase in the planned dose to 95% of the PTV of 4.0 ± 2.8 Gy (9 ± 5%) on the midposition CT (P.01). For both plans, the delivered minimum gross tumor volume (GTV) doses were greater than the planned nominal prescribed dose in all 20 patients and greater than the planned dose to 95% of the PTV in 18 (90%) patients. Nine patients (45%) had 1 or more GTVs with a delivered minimum dose more than 5 Gy higher with the midposition CT plan using dose probability PTV, compared with the delivered dose with the exhale CT plan using ITV-based PTV.For isotoxic liver SBRT planned and delivered at the mean respiratory, reduced dose probability PTV enables a mean escalation of 4 Gy (9%) in 6 fractions over ITV-based PTV. This may potentially improve local control without increasing the risk of tumor underdosing.

Purpose The accuracy of deformable image registration tools can vary widely between imaging modalities and specific implementations of the same algorithms. A biomechanical model-based algorithm initially developed in-house at an academic institution was translated into a commercial radiotherapy treatment planning system and validated for multiple imaging modalities and anatomic sites. Methods Biomechanical deformable registration (Morfeus) is a geometry-driven algorithm based on the finite element method. Boundary conditions are derived from the model-based segmentation of controlling structures in each image which establishes a point-to-point surface correspondence. For each controlling structure, material properties and fixed or sliding interfaces are assigned. The displacements of internal volumes for controlling structures and other structures implicitly deformed are solved with finite element analysis. Registration was performed for 74 patients with images (mean vector resolution) of thoracic and abdominal 4DCT (2.8 mm) and MR (5.3 mm), liver CT-MR (4.5 mm), and prostate MR (2.6 mm). Accuracy was quantified between deformed and actual target images using distance-to-agreement (DTA) for structure surfaces and the target registration error (TRE) for internal point landmarks. Results The results of the commercial implementation were as follows. The mean DTA was ≤ 1.0 mm for controlling structures and 1.0–3.5 mm for implicitly deformed structures on average. TRE ranged from 2.0 mm on prostate MR to 5.1 mm on lung MR on average, within 0.1 mm or lower than the image voxel sizes. Accuracy was not overly sensitive to changes in the material properties or variability in structure segmentations, as changing these inputs affected DTA and TRE by ≤ 0.8 mm. Maximum DTA > 5 mm occurred for 88% of the structures evaluated although these were within the inherent segmentation uncertainty for 82% of structures. Differences in accuracy between the commercial and in-house research implementations were ≤ 0.5 mm for mean DTA and ≤ 0.7 mm for mean TRE. Conclusions Accuracy of biomechanical deformable registration evaluated on a large cohort of images in the thorax, abdomen and prostate was similar to the image voxel resolution on average across multiple modalities. Validation of this treatment planning system implementation supports biomechanical deformable registration as a versatile clinical tool to enable accurate target delineation at planning and treatment adaptation.

Purpose Understanding the relationship between normal tissue dose and delayed radiation toxicity is an important component of developing more effective radiation therapy. Late outcome data are generally available only for patients who have undergone 2-dimensional (2D) treatment plans. The purpose of this study was to evaluate the accuracy of 3D normal tissue dosimetry derived from reconstructed 2D treatment plans in Hodgkin's lymphoma (HL) patients. Methods and Materials Three-dimensional lung, heart, and breast volumes were reconstructed from 2D planning radiographs for HL patients who received mediastinal radiation therapy. For each organ, a reference 3D organ was modified with patient-specific structural information, using deformable image processing software. Radiation therapy plans were reconstructed by applying treatment parameters obtained from patient records to the reconstructed 3D volumes. For each reconstructed organ mean dose (D mean ) and volumes covered by at least 5 Gy (V 5 ) and 20Gy (V 20 ) were calculated. This process was performed for 15 patients who had both 2D and 3D planning data available to compare the reconstructed normal tissue doses with those derived from the primary CT planning data and also for 10 historically treated patients with only 2D imaging available. Results For patients with 3D planning data, the normal tissue doses could be reconstructed accurately using 2D planning data. Median differences in D mean between reconstructed and actual plans were 0.18 Gy (lungs), −0.15 Gy (heart), and 0.30 Gy (breasts). Median difference in V 5 and V 20 were less than 2% for each organ. Reconstructed 3D dosimetry was substantially higher in historical mantle-field treatments than contemporary involved-field mediastinal treatments: average D mean values were 15.2 Gy vs 10.6 Gy (lungs), 27.0 Gy vs 14.3 Gy (heart), and 8.0 Gy vs 3.2 Gy (breasts). Conclusions Three-dimensional reconstruction of absorbed dose to organs at risk can be estimated accurately many years after exposure by using limited 2D data. Compared to contemporary involved-field treatments, normal tissue doses were significantly higher in historical mantle-field treatments. These methods build capacity to quantify the relationship between 3D normal tissue dose and observed late effects.

Purpose: To propose a novel technique to experimentally validate deformable dose algorithms by measuring 3D dose distributions under the condition of deformation using deformable geldosimeters produced by a novel gel fabrication method. Method: Five geldosimeters, two rigid control gels and three deformable gels, were manufactured and treated with the same conformal plan that prescribed 400 cGy to the isocenter. The control gels were treated statically; the deformable gels were treated while being compressed by an actuation device to simulate breathing motion (amplitude of compression = 1, 1.5, and 2 cm, respectively; frequency = 16 rpm). Comparison between the dose measured by the control gels and the corresponding static dose distribution calculated in the treatment planning system (TPS) has determined the intrinsic dose measurement uncertainty of the geldosimeters.Doses accumulated using MORFEUS, a biomechanical model-based deformable registration and dose accumulation algorithm, were compared with the doses measured by the deformable geldosimeters to verify the accuracy of MORFEUS using dose differences at each voxel as well as the gamma index test. Flexible plastic wraps were used to contain and protect the deformable gels from oxygen infiltration, which inhibits the gels’ dose sensitizing ability. Since the wraps were imperfect oxygen barrier, dose comparison between MORFEUS and the deformable gels was performed only in the central region with a received dose of 200 cGy or above to exclude the peripheral region where oxygen penetration had likely affected dose measurements. Results: Dose measured with the control gels showed that the intrinsic dose measurement uncertainty of the geldosimeters was 11.8 cGy or 4.7% compared to the TPS. The absolute mean voxel-by-voxel dose difference between the accumulated dose and the dose measured with the deformable gels was 4.7 cGy (SD = 36.0 cGy) or 1.5% (SD = 13.4%) for the three deformable gels. The absolute mean vector distance between the 250, 300, 350, and 400 cGy isodose surfaces on the accumulated and measured distributions was 1.2 mm (SD

Both accuracy and efficiency are critical for the implementation of biomechanical model-based deformable registration into clinical practice. The focus of this investigation is to evaluate the potential of improving the efficiency of the deformable image registration of the human lungs without loss of accuracy. Three dimensional finite element models have been developed using image data of fourteen lung cancer patients. Each model consists of two lungs, tumor, and external body. Sliding of the lungs inside the chest cavity is modeled using a frictionless surface based contact model. The effect of type of element, finite deformation and elasticity on the accuracy and computing time are investigated. Linear and quadrilateral tetrahedral elements are used with linear and nonlinear geometric analysis. Two types of material properties are applied namely: elastic and hyperelastic. The accuracy of each of the four models is examined using a number of anatomical landmarks representing the vessels bifurcation points distributed across the lungs. The registration error is not significantly affected by element type or linearity of analysis with an average vector error of around 2.8 mm. The displacement differences between linear and nonlinear analysis methods are calculated for all lungs nodes and a maximum value of 3.6 mm is found in one of the nodes near the entrance of the bronchial tree into the lungs. The 95 percentile of displacement difference ranges between 0.4 and 0.8 mm. However, the time required for the analysis is reduced from 95 min in the quadratic elements nonlinear geometry model to 3.4 min in the linear element linear geometry model. Therefore using linear tetrahedral elements with linear elastic materials and linear geometry is preferable for modeling the breathing motion of lungs for image guided radiotherapy applications.

Purpose The adoption of intensity-modulated radiotherapy (IMRT) to treat cervical malignancies has been limited in part by complex organ and tumor motion during treatment. This study explores the limits of a highly adaptive, small-margin treatment scenario to accommodate this motion. In addition, the dosimetric consequences of organ and tumor motion are modeled using a combination of deformable registration and fractional dose accumulation techniques. Methods and Materials Thirty-three cervix cancer patients had target volumes and organs-at-risk contoured on fused, pretreatment magnetic resonance–computed tomography images and weekly magnetic resonance scans taken during treatment. The dosimetric impact of interfraction organ and target motion was compared for two hypothetical treatment scenarios: a 3-mm margin plan with no replanning, and a 3-mm margin plan with an automated replan performed on the updated weekly patient geometry. Results Of the 33 patients, 24 (73%) met clinically acceptable target coverage (98% of the clinical target volume receiving at least 95% of the prescription dose) using the 3-mm margin plan without replanning. The range in dose to 98% of the clinical target volume across all patients was 7.9% of the prescription dose if no replanning was performed. After weekly replanning, this range was tightened to 2.6% of the prescription dose and all patients met clinically acceptable target coverage while maintaining organ-at-risk dose sparing. Conclusions The dosimetric impact of anatomical motion underscores the challenges of applying IMRT to treat cervix cancer. An appropriate adaptive strategy can ensure target coverage for small-margin IMRT treatments and maintain favorable organ-at-risk dose sparing.

Purpose: To investigate the effect of the bronchial tree on the accuracy of biomechanical-based deformable image registration of human lungs. Methods: Three dimensional finite element models have been developed using four dimensional computed tomography image data of ten lung cancer patients. Each model is built of a body, left and right lungs, tumor, and bronchial trees. Triangular shell elements are used for the bronchial trees while tetrahedral elements are used for other components. Hyperelastic material properties based on experimental investigation on human lungs are used for the lung parenchyma. Different material properties are assigned for the bronchial tree using five values for the modulus of elasticity of 0.01, 0.12, 0.5, 10, and 18 MPa. Lungs are modeled to slide inside chest cavities by applying frictionless contact surfaces between each lung and corresponding chest cavity. The accuracy of the models is examined using an average of 40 bronchial bifurcation points identified on inhale and exhale images. Relative accuracy is evaluated by comparing the displacement of all nodes within the lungs as well as the dosimetric difference at the exhale position predicted by the model. Results: There is no significant effect of bronchial tree on the model accuracy based on the bifurcation points analysis. However, on the local level, using an average of 38 000 nodes, there is a maximum difference of 8.5 mm in the deformation of the bronchial trees, as the modulus of elasticity of the bronchial trees increases from 0.01 to 18 MPa; however, more than 96% of nodes are within a 2.5 mm difference in each direction. The average dose difference at the predicted exhale position is less than 35 cGy between the models. Conclusions: The bronchial tree has little effect on the global deformation and the accuracy of deformable image registration of lungs. Hence, the homogenous model is a reasonable assumption. Since there are some local deformation differences between nodes as the material properties of the bronchial tree change that may affect the accuracy of dosimetric results, heterogeneity may be required for a smaller scale modeling of lungs.

Purpose: High frequency ultrasound imaging, 10-30 MHz, has the capability to assess tumor response to radiotherapy in mouse tumors as early as 24 h after treatment administration. The advantage of this technique is that the image contrast is generated by changes in the physical properties of dying cells. Therefore, a subject can be imaged before and multiple times during the treatment without the requirement of injecting specialized contrast agents. This study is motivated by a need to provide metrics of comparison between the volume and localization of cell death, assessed from histology, with the volume and localization of cell death surrogate, assessed as regions with increased echogeneity from ultrasound images. Methods: The mice were exposed to radiation doses of 2, 4, and 8 Gy. Ultrasound images were collected from each tumor before and 24 h after exposure to radiation using a broadband 25 MHz center frequency transducer. After radiotherapy, tumors exhibited hyperechoic regions in ultrasound images that corresponded to areas of cell death in histology. The ultrasound and histological images were rigidly registered. The tumors and regions of cell death were manually outlined on histological images. Similarly, the tumors and hyperechoic regions were outlined on the ultrasound images. Each setmore » of contours was converted to a volumetric mesh in order to compare the volumes and the localization of cell death in histological and ultrasound images. Results: A shrinkage factor of 17{+-}2% was calculated from the difference in the tumor volumes evaluated from histological and ultrasound images. This was used to correct the tumor and cell death volumes assessed from histology. After this correction, the average absolute difference between the volume of cell death assessed from ultrasound and histological images was 11{+-}14% and the volume overlap was 70{+-}12%. Conclusions: The method provided metrics of comparison between the volume of cell death assessed from histology and that assessed from ultrasound images. It was applied here to evaluate the capability of ultrasound imaging to assess early tumor response to radiotherapy in mouse tumors. Similarly, it can be applied in the future to evaluate the capability of ultrasound imaging to assess early tumor response to other modalities of cancer treatment. The study contributes to an understanding of the capabilities and limitation of ultrasound imaging at noninvasively detecting cell death. This provides a foundation for future developments regarding the use of ultrasound in preclinical and clinical applications to adapt treatments based on tumor response to cancer therapy.« less

Purpose: Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose-risk models could potentially be used to estimate radiotherapy-related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects. Methods: Three-dimensional planning CT images of 52 current HL patients were acquired. 12 image sets were used to construct a male and a female population lung model. 23 ''Reference'' images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient-specific lung geometry using a biomechanical-based DIR algorithm, MORFEUS. 17 ''Test'' patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges.more » Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference-adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient. Results: The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be 89.2{+-}3.9% (Right lung=88.8%; Left lung=89.6%) and 89.3{+-}2.7% (Right=88.5%; Left=90.2%), respectively. Paired T-tests demonstrated that the volumetric reconstruction method made a statistically significant improvement to the population lung model shape (p

Purpose: To find and verify the optimum sliding characteristics and material compressibility that provide the minimum error in deformable image registration of the lungs. Methods: A deformable image registration study has been conducted on a total of 16 lung cancer patients. Patient specific three dimensional finite element models have been developed to model left and right lungs, chest (body), and tumor based on 4D CT images. Contact surfaces have been applied to lung-chest cavity interfaces. Experimental test data are used to model nonlinear material properties of lungs. A parametric study is carried out on seven patients, 20 conditions for each, to investigate the sliding behavior and the tissue compressibility of lungs. Three values of coefficient of friction of 0, 0.1, and 0.2 are investigated to model lubrication and sliding restriction on the lung-chest cavity interface. The effect of material compressibility of lungs is studied using Poisson's ratios of 0.35, 0.4, 0.45, and 0.499. The model accuracy is examined by calculating the difference between the image-based displacement of bronchial bifurcation points identified in the lung images and the calculated corresponding model-based displacement. Furthermore, additional bifurcation points around the tumor and its center of mass are used to examine the effect of the mentioned parameters on the tumor localization. Results: The frictionless contact model with 0.4 Poisson's ratio provides the smallest residual errors of1.1±0.9, 1.5±1.3, and 2.1±1.6mm in the LR, AP, and SI directions, respectively. Similarly, this optimum model provides the most accurate location of the tumor with residual errors of 1.0±0.6, 0.9±0.7, and 1.4±1.0mm in all three directions. The accuracy of this model is verified on an additional nine patients with average errors of 0.8±0.7, 1.3±1.1, and 1.7±1.6mm in the LR, AP, and SI directions, respectively. Conclusions: The optimum biomechanical model with the smallest registration error is when frictionless contact model and 0.4 Poisson's ratio are applied. The overall accuracies of all bifurcation points in all 16 patients including tumor points are1.0±0.7, 1.2±1.0, and 1.7±1.4mm in the LR, AP, and SI directions, respectively.

Purpose Whole pelvic intensity-modulated radiotherapy (IMRT) is increasingly being used to treat cervix cancer and other gynecologic tumors. However, tumor and normal organ movement during treatment can substantially detract from the benefits of this approach. This study explored the effect of internal anatomic changes on the dose delivered to the tumor and organs at risk using a strategy integrating deformable soft-tissue modeling with simulated dose accumulation. Methods and Materials Twenty patients with cervix cancer underwent baseline and weekly pelvic magnetic resonance imaging during treatment. Interfraction organ motion and delivered (accumulated) dose was modeled for three treatment scenarios: four-field box, large-margin whole pelvic IMRT (20-mm planning target volume, but 10 mm inferiorly) and small-margin IMRT (5-mm planning target volume). Results Individually, the planned dose was not the same as the simulated delivered dose; however, when taken as a group, this was not statistically significant for the four-field box and large-margin IMRT plans. The small-margin IMRT plans yielded adequate target coverage in most patients; however, significant target underdosing occurred in 1 patient who displayed excessive, unpredictable internal target movement. The delivered doses to the organs at risk were significantly reduced with the small-margin plan, although substantial variability was present among the patients. Conclusion Simulated dose accumulation might provide a more accurate depiction of the target and organ at risk coverage during fractionated whole pelvic IMRT for cervical cancer. The adequacy of primary tumor coverage using 5-mm planning target volume margins is contingent on the use of daily image-guided setup.

Deformable registration can improve the accuracy of tumor targeting; however for online applications, efficiency as well as accuracy is important. A navigator channel technique has been developed to combine a biomechanical model-based deformable registration algorithm with a population motion model and patient specific motion information to perform fast deformable registration for application in image-guided radiation therapy. A respiratory population-based liver motion model was generated from breath-hold CT data sets of ten patients using a finite element model as a framework. The population model provides a biomechanical reference template of the average liver motions, which were found to be (absolute mean±SD) 0.12±0.10, 0.84±0.13, and 1.24±0.18 cm in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions, respectively. The population motion model was then adapted to the specific liver motion of 13 patients based on their exhale and inhale CT images. The patient motion was calculated using a navigator channel (a narrow region of interest window) on liver boundaries in the images. The absolute average accuracy of the navigator channel to predict the 1D SI and AP motions of the liver was less than 0.11, which is less than the out-of-plane image voxel size, 0.25 cm. This 1D information was then used to adapt the 4D population motion model in the SI and AP directions to predict the patient specific liver motion. The absolute average residual error of the navigator channel technique to adapt the population motion to the patients’ specific motion was verified using three verification methods: (1) vessel bifurcation, (2) tumor center of mass, and (3) MORFEUS deformable algorithm. All three verification methods showed statistically similar results where the technique’s accuracy was approximately on the order of the voxel image sizes. This method has potential applications in online assessment of motion at the time of treatment to improve image-guided radiotherapy and monitoring of intrafraction motion.

Purpose: Evaluate the accuracy and the sensitivity to contour variation and model size of a finite element model-based deformable registration algorithm for the prostate. Methods and materials: Two magnetic resonance images (MRIs) were obtained for 21 prostate patients with three implanted markers. A single observer contoured the prostate and markers and performed blinded recontouring of the first MRI. A biomechanical-model based deformable registration algorithm, MORFEUS, was applied to each dataset pair, deforming the second image (B) to the first image (A). The residual error was calculated by comparing the center of mass (COM) of the markers with the predicted COM. Sensitivity to contour variation was calculated by deforming B to the repeat contour of A (A2). The sensitivity to the model size was calculated by reducing the number of nodes (B′, A′, A2′) and repeating the analysis. Results: The average residual error of the registration for B to A and B to A2 was 0.22cm (SD: 0.08cm) and 0.24cm (SD: 0.09cm), respectively. The average residual error of the registration of B′ to A′ and B′ to A2′ was 0.22cm (SD: 0.10cm) and 0.25cm (SD: 0.10cm), respectively. The average time to run MORFEUS on the standard and reduced model was 3606s (SD: 7788s) and 56s (SD: 16s), respectively. Conclusions: The accuracy of the algorithm, equal to the image voxel size, is not affected by intraobserver contour variability or model size. Reducing the model size significantly increases algorithm efficiency.

Purpose: Endorectal coil (ERC) magnetic resonance imaging (MRI) provides superior visualization of the prostate compared with computed tomography at the expense of deformation. This study aimed to develop a multiorgan finite element deformable method, Morfeus, to accurately co-register these images for radiotherapy planning. Methods: Patients with prostate cancer underwent fiducial marker implantation and computed tomography simulation for radiotherapy planning. A series of axial MRI scans were acquired with and without an ERC. The prostate, bladder, rectum, and pubic bones were manually segmented and assigned linear elastic material properties. Morfeus mapped the surface of the bladder and rectum between two imaged states, calculating the deformation of the prostate through biomechanical properties. The accuracy of deformation was measured as fiducial marker error and residual surface deformation between the inferred and actual prostate. The deformation map was inverted to deform from 100 cm 3 to no coil. Results: The data from 19 patients were analyzed. Significant prostate deformation occurred with the ERC (mean intrapatient range, 0.88 ± 0.25 cm). The mean vector error in fiducial marker position ( n = 57) was 0.22 ± 0.09 cm, and the mean vector residual surface deformation ( n = 19) was 0.15 ± 0.06 cm for deformation from no coil to 100-cm 3 ERC, with an image vector resolution of 0.22 cm. Accurately deformed MRI scans improved soft-tissue resolution of the anatomy for radiotherapy planning. Conclusions: This method of multiorgan deformable registration enabled accurate co-registration of ERC-MRI scans with computed tomography treatment planning images. Superior structural detail was visible on ERC-MRI, which has potential for improving target delineation.

Purpose The application of a biomechanical deformable image registration algorithm has been demonstrated to overcome the potential limitations in the use of intensity-based algorithms on low-contrast images that lack prominent features. Because validation of deformable registration is particularly challenging on such images, the dose distribution predicted via a biomechanical algorithm was evaluated using the measured dose from a deformable dosimeter. Methods and materials A biomechanical model–based image registration algorithm registered computed tomographic (CT) images of an elastic radiochromic dosimeter between its undeformed and deformed positions. The algorithm aligns the external boundaries of the dosimeter, created from CT contours, and the internal displacements are solved by modeling the physical material properties of the dosimeter. The dosimeter was planned and irradiated in its deformed position, and subsequently, the delivered dose was measured with optical CT in the undeformed position. The predicted dose distribution, created by applying the deformable registration displacement map to the planned distribution, was then compared with the measured optical CT distribution. Results Compared with the optical CT distribution, biomechanical image registration predicted the position and size of the deformed dose fields with mean errors of ≤1 mm (maximum, 3 mm). The accuracy did not differ between cross sections with a greater or lesser deformation magnitude despite the homogenous CT intensities throughout the dosimeter. The overall 3-dimensional voxel passing rate of the predicted distribution was γ3%/3mm = 91% compared with optical CT. Conclusions Biomechanical registration accurately predicted the deformed dose distribution measured in a deformable dosimeter, whereas previously, evaluations of a commercial intensity-based algorithm demonstrated substantial errors. The addition of biomechanical algorithms to the collection of adaptive radiation therapy tools would be valuable for dose accumulation, particularly in feature-poor images such as cone beam CT and organs such as the liver.

Purpose: We have measured the variability in identifying geometric errors and the variability in clinical decision making when using portal films. Methods and Materials: Eight observers (four radiation oncologists and four radiation therapists) viewed 40 film pairs from 40 different patients. All films, which were acquired using conventional simulator and portal film cassettes, were selected retrospectively from a large clinical database. The observers compared the simulator and portal films under standard conditions, identified the field placement errors, and decided whether adjustments in treatment were required. In addition, all films were digitized and the field placement errors were measured objectively using image registration software. Results: There was much variability in identifying field placement errors and even more variability in the number of recommended adjustments. The field placement errors identified by the different observers differed by up to 50 mm for the same film pair. The number of adjustments of treatment or block position recommended by the observers also varied between 8 and 25 for the same set of films. The average field placement error, before correction, for AP lung, AP pelvis, and lateral pelvis films was 5.7 mm, 6.3 mm, and 8.9 mm, while the average error after correction (i.e., correcting all errors identified by the observers) was 5.5 mm, 4.9 mm, and 5.7 mm, respectively. Thus, for lateral pelvis films, where the initial errors were larger, the observers were able to make an improvement in patient setup. Conclusions: The results suggest that human observers have difficulty identifying field placement errors accurately when the errors are around 5 mm or smaller. Although there is some evidence that experience influenced the performance of the observers, the effect of experience is not large. In routine clinical environments, the use of visual inspection will detect large field placement errors. However, tools other than visual inspection will be required if field placement errors 5 mm or smaller are to be identified accurately.

Purpose Establishing the time-weighted mean respiratory position in the liver is challenging due to poor tumor contrast on 4-dimensional (4D) imaging. The purpose of this study is to validate simplified strategies in determining the mean position of liver tumors for radiation therapy planning, and quantify the potential for planning target volume (PTV) reduction. Methods and materials Full, 10-phase 4D computed tomography (CT) data sets from 10 liver radiation therapy patients were analyzed to compare 2 techniques. First, a mid-ventilation CT was chosen from the initial reconstruction of the 4DCT. This was based on the minimum displacement of the diaphragm at each phase relative to its mean respiratory position, calculated using rigid registration over all 4DCT phases. Second, the exhale 4DCT was deformed to the inhale 4DCT using biomechanical-based deformable registration. The diaphragm's mean cranio-caudal position in the respiratory cycle (normalized as a percentage relative to exhale) was applied to the exhale-to-inhale deformation map assuming a linear trajectory to reconstruct a mid-position CT. These strategies were compared with the time-weighted mean respiratory position, calculated with deformable registration over all 10 4DCT phases. PTVs incorporating respiratory motion were then compared for 2 planning strategies: exhale 4DCT using the internal target volume (ITV), or mid-position CT using dose-probability margins. Results Compared with the mean respiratory tumor position, the mid-ventilation CT and mid-position CT had mean (maximum) tumor vector errors of 1.0 ± 0.5 (2.1) mm and 0.6 ± 0.3 (1.4) mm, respectively, within the image resolution. Compared with ITV-based PTV, dose-probability PTV reduced the irradiated volume by 34% ± 7% on average, up to 43%. Conclusions Simplified strategies to select a mid-ventilation CT or reconstruct a mid-position CT for the liver were validated with respect to the mean respiratory position. These data sets require significantly smaller PTVs, potentially allowing for dose-escalated liver stereotactic body radiation therapy to improve local control.

Purpose: We have developed a semi-automated dose accumulation workflow for Head and Neck Cancer (HNC) patients to evaluate volumetric and dosimetric changes that take place during radiotherapy. This work will be used to assess how dosimetric changes affect both toxicity and disease control, hence inform the feasibility and design of a prospective HNC adaptive trial. Methods: RayStation 4.5.2 features deformable image registration (DIR), where structures already defined on the planning CT image set can be deformably mapped onto cone-beam computed tomography (CBCT) images, accounting for daily treatment set-up shifts and changes in patient anatomy. The daily delivered dose can be calculated on each CBCT and mapped back to the planning CT to allow dose accumulation. The process is partially automated using Python scripts developed in collaboration with RaySearch. Results: To date we have performed dose accumulation on 18 HNC patients treated at our institution during 2013–2015 under REB approval. Our semi-automated process establishes clinical feasibility. Generally, dose accumulation for the entire treatment course of one case takes 60–120 minutes: importing all CBCTs requires 20–30 minutes as each patient has 30 to 40 treated fractions; image registration and dose accumulation require 60–90 minutes. This is in contrast to the process without automated scripts where dose accumulation alone would take 3–5 hours. Conclusions: We have developed a reliable workflow for retrospective dose tracking in HNC using RayStation. The process has been validated for HNC patients treated on both Elekta and Varian linacs with CBCTs acquired on XVI and OBI platforms respectively.

Purpose Substantial organ motion and tumor shrinkage occur during radiotherapy for cervix cancer. IMRT planning studies have shown that the quality of radiation delivery is influenced by these anatomical changes, therefore the adaptation of treatment plans may be warranted. Image guidance with off-line replanning, i.e. hybrid-adaptation, is recognized as one of the most practical adaptation strategies. In this study, we investigated the effects of soft tissue image guidance using on-line MR while varying the frequency of off-line replanning on the adaptation of cervix IMRT. Materials and method 33 cervical cancer patients underwent planning and weekly pelvic MRI scans during radiotherapy. 5 patients of 33 were identified in a previous retrospective adaptive planning study, in which the coverage of gross tumor volume/clinical target volume (GTV/CTV) was not acceptable given single off-line IMRT replan using a 3 mm PTV margin with bone matching. These 5 patients and a randomly selected 10 patients from the remaining 28 patients, a total of 15 patients of 33, were considered in this study. Two matching methods for image guidance (bone to bone and soft tissue to dose matrix) and three frequencies of off-line replanning (none, single, and weekly) were simulated and compared with respect to target coverage (cervix, GTV, lower uterus, parametrium, upper vagina, tumor related CTV and elective lymph node CTV) and OAR sparing (bladder, bowel, rectum, and sigmoid). Cost (total process time) and benefit (target coverage) were analyzed for comparison. Results Hybrid adaptation (image guidance with off-line replanning) significantly enhanced target coverage for both 5 difficult and 10 standard cases. Concerning image guidance, bone matching was short of delivering enough doses for 5 difficult cases even with a weekly off-line replan. Soft tissue image guidance proved successful for all cases except one when single or more frequent replans were utilized in the difficult cases. Cost and benefit analysis preferred (soft tissue) image guidance over (frequent) off-line replanning. Conclusions On-line MRI based image guidance (with combination of dose distribution) is a crucial element for a successful hybrid adaptive radiotherapy. Frequent off-line replanning adjuvantly enhances adaptation quality.

Purpose To investigate the accumulated dose deviations to tumors and normal tissues in liver stereotactic body radiotherapy (SBRT) and investigate their geometric causes. Methods and Materials Thirty previously treated liver cancer patients were retrospectively evaluated. Stereotactic body radiotherapy was planned on the static exhale CT for 27–60 Gy in 6 fractions, and patients were treated in free-breathing with daily cone-beam CT guidance. Biomechanical model-based deformable image registration accumulated dose over both the planning four-dimensional (4D) CT (predicted breathing dose) and also over each fraction's respiratory-correlated cone-beam CT (accumulated treatment dose). The contribution of different geometric errors to changes between the accumulated and predicted breathing dose were quantified. Results Twenty-one patients (70%) had accumulated dose deviations relative to the planned static prescription dose >5%, ranging from −15% to 5% in tumors and −42% to 8% in normal tissues. Sixteen patients (53%) still had deviations relative to the 4D CT–predicted dose , which were similar in magnitude. Thirty-two tissues in these 16 patients had deviations >5% relative to the 4D CT–predicted dose, and residual setup errors ( n = 17) were most often the largest cause of the deviations, followed by deformations ( n = 8) and breathing variations ( n = 7). Conclusion The majority of patients had accumulated dose deviations >5% relative to the static plan. Significant deviations relative to the predicted breathing dose still occurred in more than half the patients, commonly owing to residual setup errors. Accumulated SBRT dose may be warranted to pursue further dose escalation, adaptive SBRT, and aid in correlation with clinical outcomes.

Purpose To investigate the effect of breathing motion and dose accumulation on the planned radiotherapy dose to liver tumors and normal tissues using deformable image registration. Methods and Materials Twenty-one free-breathing stereotactic liver cancer radiotherapy patients, planned on static exhale computed tomography (CT) for 27–60 Gy in six fractions, were included. A biomechanical model–based deformable image registration algorithm retrospectively deformed each exhale CT to inhale CT. This deformation map was combined with exhale and inhale dose grids from the treatment planning system to accumulate dose over the breathing cycle. Accumulation was also investigated using a simple rigid liver-to-liver registration. Changes to tumor and normal tissue dose were quantified. Results Relative to static plans, mean dose change (range) after deformable dose accumulation (as % of prescription dose) was −1 (−14 to 8) to minimum tumor, −4 (−15 to 0) to maximum bowel, −4 (−25 to 1) to maximum duodenum, 2 (−1 to 9) to maximum esophagus, −2 (−13 to 4) to maximum stomach, 0 (−3 to 4) to mean liver, and −1 (−5 to 1) and −2 (−7 to 1) to mean left and right kidneys. Compared to deformable registration, rigid modeling had changes up to 8% to minimum tumor and 7% to maximum normal tissues. Conclusion Deformable registration and dose accumulation revealed potentially significant dose changes to either a tumor or normal tissue in the majority of cases as a result of breathing motion. These changes may not be accurately accounted for with rigid motion.

Deformable image registration of four head and neck cancer patients was conducted using biomechanical based model. Patient specific 3D finite element models have been developed using CT and cone beam CT image data of the planning and a radiation treatment session. The model consists of seven vertebrae (C1 to C7), mandible, larynx, left and right parotid glands, tumor and body. Different combinations of boundary conditions are applied in the model in order to find the configuration with a minimum registration error. Each vertebra in the planning session is individually aligned with its correspondence in the treatment session. Rigid alignment is used for each individual vertebra and to the mandible since deformation is not expected in the bones. In addition, the effect of morphological differences in external body between the two image sessions is investigated. The accuracy of the registration is evaluated using the tumor, and left and right parotid glands by comparing the calculated Dice similarity index of these structures following deformation in relation to their true surface defined in the image of the second session. The registration improves when the vertebrae and mandible are aligned in the two sessions with the highest Dice index of 0.86±0.08, 0.84±0.11, and 0.89±0.04 for the tumor, left and right parotid glands, respectively. The accuracy of the center of mass location of tumor and parotid glands is also improved by deformable image registration where the error in the tumor and parotid glands decreases from 4.0±1.1, 3.4±1.5, and 3.8±0.9 mm using rigid registration to 2.3±1.0, 2.5±0.8 and 2.0±0.9 mm in the deformable image registration when alignment of vertebrae and mandible is conducted in addition to the surface projection of the body.

Purpose To assess the movement of rectum, mesorectum, and rectal primary during a course of preoperative chemoradiotherapy. Methods and Materials Seventeen patients with Stage II or III rectal cancer had a planning CT scan with rectal contrast before commencement of preoperative chemoradiation. The scan was repeated during Weeks 1, 3, and 5 of chemoradiation. The rectal primary (gross tumor volume), rectum, mesorectum, and bladder were contoured on all four scans. An in-house biomechanical model-based deformable image registration technique, Morfeus, was used to measure the three-dimensional spatial change in these structures after bony alignment. The required planning target volume margin for this spatial change, after bone alignment, was also calculated. Results Rectal contrast was found to introduce a systematic error in the position of all organs compared with the noncontrast state. The largest change in structures during radiotherapy was in the anterior and posterior directions for the mesorectum and rectum and in the superior and inferior directions for the gross tumor volume. The planning target volume margins required for internal movement for the mesorectum based on the three scans acquired during treatment are 4 mm right, 5 mm left, 7 mm anterior, and 6 mm posterior. For the rectum, values were 8 mm right, 8 mm left, 8 mm anterior, and 9 mm posterior. The greatest movement of the rectum occurred in the upper third. Conclusions Contrast is no longer used in CT simulation. Assuming bony alignment, a nonuniform margin of 8 mm anteriorly, 9 mm posteriorly, and 8 mm left and right is recommended.

Patient specific 3D finite element models have been developed using 4DCT (3D+time) image data for 5 liver cancer patients. Each model consists of the liver, tumors, left and right kidneys, stomach, spleen and body. Breathing motion of the liver, spleen and body is found and applied as displacement boundary conditions in the model. Sliding of the liver relative to the surrounding tissues is modeled using frictionless contact surfaces. Landmarks representing vessels bifurcation inside the liver are used for the model accuracy test. The goal of the study is to examine the effect of contact surface model on the performance of the deformable image registration of the liver. The accuracy of the model is improved by applying contact surface. Substantial displacement differences are observed between models with and without contact surface of the liver. The largest difference is in the Superior-Inferior (SI) followed by Anterior-Posterior (AP).